December 4, 2018

Slides: https://github.com/NHS-NSS-transforming-publications/RAP-presentation

RAP companion: https://ukgovdatascience.github.io/rap_companion/

Reproducible research

  • Not a new concept
  • Encouraged and growing within academia for last 10-15 years
  • Provides evidence of the correctness of results
  • Exposes workflow to others
  • Enables others to make use of methods and results

Current publication process

  • Complex (many steps between software)
  • Prone to error
  • Manual, menial tasks carried out by highly skilled people
  • Not reproducible or sustainable

The solution

RAP companion

Combined the priniciples of reproducible research with data science tools and best practice.

Why R?

What is RAP?

Transforming Publishing test case: Hospital Standardised Mortality
Ratio publication

Levels of automation

Level Description
1 Ad hoc R code
2 R project
3 R project under version control (VC)
4a R project under VC and peer reviewed (wrangling)
4b Replicable report in Rmarkdown (publication)
5 Near RAP (VC, peer review, data quality assurance)
6 Full RAP (as above plus unit testing and documentation)
7 R package

Challenges

  • Culture change (peer review and working in the open)
  • New software such as R and git
  • Required development time
  • Range of data sources and/or unstable production process
  • IT (R server and internally hosted code repository)

Interested in RAP?…

  • How many reports do your team produce?
  • What proportion of time is spent producing reports?
  • How much copying and pasting/data movement between software is involved?
  • What proportion of your spreadsheet or report contains errors?
  • What would the impact of mistakes in production be?
  • Could your team create the report if certain team members suddenly left?
  • Could you reproduce your publication statistics from 5 years ago?

Contact the Transforming Publishing team (nss.isdtransformingpublishing@nhs.net)

Thank You